Drying of black cumin (Nigella sativa) in a microwave assisteddrying system and modeling using extreme learning machine. Energy, 44,352-357
[ X ]
Tarih
2012
Yazarlar
Dergi Başlığı
Dergi ISSN
Cilt Başlığı
Yayıncı
Erişim Hakkı
info:eu-repo/semantics/openAccess
Özet
Abstract Drying characteristics of Black cumin seeds (BCs) (Nigella sativa) with initial moisture content 58.14% (d.b) was investigated in microwave assisted drying system. The experiments were carried out in two aspects which were the BCs drying with different temperatures (35, 40 and 50 °C) and different microwave power levels (250, 500 and 750 W). The results showed that the drying rates of BCs have high efficiency with drying temperatures at constant microwave power level. Furthermore, in present study, the applications of Extreme Learning Machine (ELM) and Artificial Neural Network (ANN) for predicting the moisture ratio (MR) (output feature for ELM modeling) were investigated. Microwave temperature, microwave power and drying time were input layer features for the modeling. An ELM model by 93 neurons with Sine transfer function in hidden layer was selected. The results revealed that a network with the Sine function made the most accurate prediction for the BCs drying system. For BCs all data set, maximum R2 and minimum RMSE (root mean square error) were found as 0.9987 and 0.0123, respectively.
Açıklama
Anahtar Kelimeler
Black cumin; Microwave; Drying; Modeling; ELM
